{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\au282143\Desktop\PSRM\Replication\Log for Are Pro-Im.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}10 Jul 2024, 10:09:42

{com}. do "C:\Users\au282143\AppData\Local\Temp\STD2610_000000.tmp"
{txt}
{com}. ******CODE TO REPLICATE ANALYSES FOR "ARE PRO-IMMIGRANT MESSAGES INEFFECTIVE?"******
. 
. *****SETTING COLOR SCHEME*****
. set scheme plotplain
{txt}
{com}. 
. *****GENERATING RELEVANT VARIABLES*****
. ***Party camp***
. gen party_camp = 1 if q6==1 | q6==2 | q6==6 | q8==1 | q8==2 | q8==6 
{txt}(1,254 missing values generated)

{com}. replace party_camp = 2 if q6==11 | q6==3 | q6==7 | q8==11 | q8==3 | q8==7 
{txt}(429 real changes made)

{com}. replace party_camp = 3 if q6==12 | q6==13 | q8==12 | q8==13
{txt}(205 real changes made)

{com}. replace party_camp = 4 if q6==4 | q6==9 | q6==10 | q8==4 | q8==9 | q8==10
{txt}(245 real changes made)

{com}. recode party_camp (1=1) (2=2) (3=3) (4=4) (else=0)
{txt}(375 changes made to {bf:party_camp})

{com}. 
. label define partycamp 0"None" 1"SD camp" 2"V camp" 3"Extreme left" 4"Extreme right"
{txt}
{com}. label values party_camp partycamp 
{txt}
{com}. 
. *****TESTING H1A-H1C*****
. ***Table 1***
. putdocx begin
{res}{txt}
{com}. reg q15 i.message

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,563
{txt}{hline 13}{c +}{hline 34}   F(3, 1559)      = {res}     5.11
{txt}       Model {c |} {res} 19.6534623         3   6.5511541   {txt}Prob > F        ={res}    0.0016
{txt}    Residual {c |} {res} 1997.79503     1,559  1.28145929   {txt}R-squared       ={res}    0.0097
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0078
{txt}       Total {c |} {res}  2017.4485     1,562  1.29158034   {txt}Root MSE        =   {res}  1.132

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           q15{col 16}{c |} Coefficient{col 28}  Std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}message {c |}
{space 4}Pro_moral  {c |}{col 16}{res}{space 2}  .177913{col 28}{space 2} .0814316{col 39}{space 1}    2.18{col 48}{space 3}0.029{col 56}{space 4}  .018186{col 69}{space 3}   .33764
{txt}Anti_nonmoral  {c |}{col 16}{res}{space 2} .3034139{col 28}{space 2} .0804212{col 39}{space 1}    3.77{col 48}{space 3}0.000{col 56}{space 4} .1456688{col 69}{space 3}  .461159
{txt}{space 3}Anti_moral  {c |}{col 16}{res}{space 2} .2292272{col 28}{space 2} .0815377{col 39}{space 1}    2.81{col 48}{space 3}0.005{col 56}{space 4} .0692921{col 69}{space 3} .3891624
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} 2.674419{col 28}{space 2} .0575436{col 39}{space 1}   46.48{col 48}{space 3}0.000{col 56}{space 4} 2.561548{col 69}{space 3}  2.78729
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. putdocx table table1 = etable, width(100%)
{res}{txt}
{com}. putdocx save table1
{res}successfully created {browse "C:/Users/au282143/Desktop/PSRM/Replication/table1.docx":"C:/Users/au282143/Desktop/PSRM/Replication/table1.docx"}
{txt}
{com}. 
. *****TESTING H2*****
. ***Figure 1, left panel***
. reg q15 i.message##i.partysponsor if party_camp==1

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       502
{txt}{hline 13}{c +}{hline 34}   F(7, 494)       = {res}     6.31
{txt}       Model {c |} {res} 45.0045636         7  6.42922337   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 503.186671       494   1.0185965   {txt}R-squared       ={res}    0.0821
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0691
{txt}       Total {c |} {res} 548.191235       501  1.09419408   {txt}Root MSE        =   {res} 1.0093

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   q15{col 24}{c |} Coefficient{col 36}  Std. err.{col 48}      t{col 56}   P>|t|{col 64}     [95% con{col 77}f. interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}message {c |}
{space 12}Pro_moral  {c |}{col 24}{res}{space 2} .1220401{col 36}{space 2} .1812912{col 47}{space 1}    0.67{col 56}{space 3}0.501{col 64}{space 4}-.2341569{col 77}{space 3}  .478237
{txt}{space 8}Anti_nonmoral  {c |}{col 24}{res}{space 2} -.248538{col 36}{space 2} .1719616{col 47}{space 1}   -1.45{col 56}{space 3}0.149{col 64}{space 4}-.5864043{col 77}{space 3} .0893283
{txt}{space 11}Anti_moral  {c |}{col 24}{res}{space 2}-.4183007{col 36}{space 2}  .190107{col 47}{space 1}   -2.20{col 56}{space 3}0.028{col 64}{space 4}-.7918187{col 77}{space 3}-.0447826
{txt}{space 22} {c |}
{space 10}partysponsor {c |}
{space 14}Venstre  {c |}{col 24}{res}{space 2}-.3601533{col 36}{space 2} .1836579{col 47}{space 1}   -1.96{col 56}{space 3}0.050{col 64}{space 4}-.7210001{col 77}{space 3} .0006936
{txt}{space 22} {c |}
{space 2}message#partysponsor {c |}
{space 4}Pro_moral#Venstre  {c |}{col 24}{res}{space 2}-.0686161{col 36}{space 2} .2545092{col 47}{space 1}   -0.27{col 56}{space 3}0.788{col 64}{space 4}-.5686701{col 77}{space 3}  .431438
{txt}Anti_nonmoral#Venstre  {c |}{col 24}{res}{space 2} .0644351{col 36}{space 2} .2537659{col 47}{space 1}    0.25{col 56}{space 3}0.800{col 64}{space 4}-.4341585{col 77}{space 3} .5630288
{txt}{space 3}Anti_moral#Venstre  {c |}{col 24}{res}{space 2} -.142181{col 36}{space 2}  .264331{col 47}{space 1}   -0.54{col 56}{space 3}0.591{col 64}{space 4}-.6615327{col 77}{space 3} .3771707
{txt}{space 22} {c |}
{space 17}_cons {c |}{col 24}{res}{space 2} 3.222222{col 36}{space 2} .1271542{col 47}{space 1}   25.34{col 56}{space 3}0.000{col 64}{space 4} 2.972392{col 77}{space 3} 3.472052
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. pwcompare message#partysponsor, group
{res}
{txt}Pairwise comparisons of marginal linear predictions

{txt}{p2colset 1 10 10 2}{...}
{p2col:Margins:}{res:asbalanced}{p_end}
{p2colreset}{...}

{res}{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 3}{hline 10}
{col 24}{c |}{col 50}Unadjusted
{col 24}{c |}     Margin{col 36}   Std. err.{col 50}    groups
{hline 23}{c +}{hline 11}{hline 11}{hline 3}{hline 10}
{space 2}message#partysponsor {c |}
{space 2}Pro_nonmoral#SocDem  {c |}{col 24}{res}{space 2} 3.222222{col 36}{space 2} .1271542{col 50}{txt}        BC
{space 1}Pro_nonmoral#Venstre  {c |}{col 24}{res}{space 2} 2.862069{col 36}{space 2} .1325217{col 50}{txt}       AB 
{space 5}Pro_moral#SocDem  {c |}{col 24}{res}{space 2} 3.344262{col 36}{space 2} .1292219{col 50}{txt}         C
{space 4}Pro_moral#Venstre  {c |}{col 24}{res}{space 2} 2.915493{col 36}{space 2} .1197766{col 50}{txt}       AB 
{space 1}Anti_nonmoral#SocDem  {c |}{col 24}{res}{space 2} 2.973684{col 36}{space 2} .1157695{col 50}{txt}       AB 
Anti_nonmoral#Venstre  {c |}{col 24}{res}{space 2} 2.677966{col 36}{space 2} .1313939{col 50}{txt}       A  
{space 4}Anti_moral#SocDem  {c |}{col 24}{res}{space 2} 2.803922{col 36}{space 2}  .141324{col 50}{txt}       A  
{space 3}Anti_moral#Venstre  {c |}{col 24}{res}{space 2} 2.301587{col 36}{space 2} .1271542
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 3}{hline 10}
{p 0 6 0 59}Note: Margins sharing a letter in the group label are not significantly different at the 5% level. {p_end}

{com}. cibar q15 if party_camp==1, over1(partysponsor) over2(message) barcol(gs3 gs11) graphopt(ytitle("") yscale(range(1 (1) 5)) ylab(1 (1) 5))
{res}{txt}
{com}. graph export fig1a.png
{txt}{p 0 4 2}
file {bf}
fig1a.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. ***Figure 1, right panel*** 
. reg q15 i.message##i.partysponsor if party_camp==2

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       399
{txt}{hline 13}{c +}{hline 34}   F(7, 391)       = {res}    14.19
{txt}       Model {c |} {res} 88.0705905         7  12.5815129   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 346.626151       391  .886511896   {txt}R-squared       ={res}    0.2026
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1883
{txt}       Total {c |} {res} 434.696742       398  1.09220287   {txt}Root MSE        =   {res} .94155

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                   q15{col 24}{c |} Coefficient{col 36}  Std. err.{col 48}      t{col 56}   P>|t|{col 64}     [95% con{col 77}f. interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}message {c |}
{space 12}Pro_moral  {c |}{col 24}{res}{space 2}   .18438{col 36}{space 2}  .188915{col 47}{space 1}    0.98{col 56}{space 3}0.330{col 64}{space 4}-.1870363{col 77}{space 3} .5557963
{txt}{space 8}Anti_nonmoral  {c |}{col 24}{res}{space 2} 1.243386{col 36}{space 2} .1937119{col 47}{space 1}    6.42{col 56}{space 3}0.000{col 64}{space 4}  .862539{col 77}{space 3} 1.624234
{txt}{space 11}Anti_moral  {c |}{col 24}{res}{space 2} .9398148{col 36}{space 2} .1739788{col 47}{space 1}    5.40{col 56}{space 3}0.000{col 64}{space 4} .5977638{col 77}{space 3} 1.281866
{txt}{space 22} {c |}
{space 10}partysponsor {c |}
{space 14}Venstre  {c |}{col 24}{res}{space 2} .8532764{col 36}{space 2} .1829349{col 47}{space 1}    4.66{col 56}{space 3}0.000{col 64}{space 4} .4936172{col 77}{space 3} 1.212936
{txt}{space 22} {c |}
{space 2}message#partysponsor {c |}
{space 4}Pro_moral#Venstre  {c |}{col 24}{res}{space 2} .0271584{col 36}{space 2} .2668449{col 47}{space 1}    0.10{col 56}{space 3}0.919{col 64}{space 4}-.4974719{col 77}{space 3} .5517887
{txt}Anti_nonmoral#Venstre  {c |}{col 24}{res}{space 2}-.9289066{col 36}{space 2} .2682447{col 47}{space 1}   -3.46{col 56}{space 3}0.001{col 64}{space 4}-1.456289{col 77}{space 3}-.4015243
{txt}{space 3}Anti_moral#Venstre  {c |}{col 24}{res}{space 2}-.3592287{col 36}{space 2} .2615805{col 47}{space 1}   -1.37{col 56}{space 3}0.170{col 64}{space 4} -.873509{col 77}{space 3} .1550516
{txt}{space 22} {c |}
{space 17}_cons {c |}{col 24}{res}{space 2} 2.185185{col 36}{space 2} .1281284{col 47}{space 1}   17.05{col 56}{space 3}0.000{col 64}{space 4} 1.933278{col 77}{space 3} 2.437092
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. pwcompare message#partysponsor, group 
{res}
{txt}Pairwise comparisons of marginal linear predictions

{txt}{p2colset 1 10 10 2}{...}
{p2col:Margins:}{res:asbalanced}{p_end}
{p2colreset}{...}

{res}{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 3}{hline 10}
{col 24}{c |}{col 50}Unadjusted
{col 24}{c |}     Margin{col 36}   Std. err.{col 50}    groups
{hline 23}{c +}{hline 11}{hline 11}{hline 3}{hline 10}
{space 2}message#partysponsor {c |}
{space 2}Pro_nonmoral#SocDem  {c |}{col 24}{res}{space 2} 2.185185{col 36}{space 2} .1281284{col 50}{txt}      A   
{space 1}Pro_nonmoral#Venstre  {c |}{col 24}{res}{space 2} 3.038462{col 36}{space 2} .1305692{col 50}{txt}       B  
{space 5}Pro_moral#SocDem  {c |}{col 24}{res}{space 2} 2.369565{col 36}{space 2} .1388236{col 50}{txt}      A   
{space 4}Pro_moral#Venstre  {c |}{col 24}{res}{space 2}     3.25{col 36}{space 2} .1359007{col 50}{txt}       BCD
{space 1}Anti_nonmoral#SocDem  {c |}{col 24}{res}{space 2} 3.428571{col 36}{space 2} .1452839{col 50}{txt}        CD
Anti_nonmoral#Venstre  {c |}{col 24}{res}{space 2} 3.352941{col 36}{space 2}  .131843{col 50}{txt}       BCD
{space 4}Anti_moral#SocDem  {c |}{col 24}{res}{space 2}    3.125{col 36}{space 2} .1176935{col 50}{txt}       BC 
{space 3}Anti_moral#Venstre  {c |}{col 24}{res}{space 2} 3.619048{col 36}{space 2} .1452839{col 50}{txt}         D
{hline 23}{c BT}{hline 11}{hline 11}{hline 3}{hline 10}
{p 0 6 0 59}Note: Margins sharing a letter in the group label are not significantly different at the 5% level. {p_end}

{com}. cibar q15 if party_camp==2, over1(partysponsor) over2(message) barcol(gs3 gs11) graphopt(ytitle("") yscale(range(1 (1) 5)) ylab(1 (1) 5))
{res}{txt}
{com}. graph export fig1b.png
{txt}{p 0 4 2}
file {bf}
fig1b.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. *****APPENDIX*****
. ***Figure A2.1.***
. reg q15 i.message

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,563
{txt}{hline 13}{c +}{hline 34}   F(3, 1559)      = {res}     5.11
{txt}       Model {c |} {res} 19.6534623         3   6.5511541   {txt}Prob > F        ={res}    0.0016
{txt}    Residual {c |} {res} 1997.79503     1,559  1.28145929   {txt}R-squared       ={res}    0.0097
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0078
{txt}       Total {c |} {res}  2017.4485     1,562  1.29158034   {txt}Root MSE        =   {res}  1.132

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           q15{col 16}{c |} Coefficient{col 28}  Std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}message {c |}
{space 4}Pro_moral  {c |}{col 16}{res}{space 2}  .177913{col 28}{space 2} .0814316{col 39}{space 1}    2.18{col 48}{space 3}0.029{col 56}{space 4}  .018186{col 69}{space 3}   .33764
{txt}Anti_nonmoral  {c |}{col 16}{res}{space 2} .3034139{col 28}{space 2} .0804212{col 39}{space 1}    3.77{col 48}{space 3}0.000{col 56}{space 4} .1456688{col 69}{space 3}  .461159
{txt}{space 3}Anti_moral  {c |}{col 16}{res}{space 2} .2292272{col 28}{space 2} .0815377{col 39}{space 1}    2.81{col 48}{space 3}0.005{col 56}{space 4} .0692921{col 69}{space 3} .3891624
{txt}{space 14} {c |}
{space 9}_cons {c |}{col 16}{res}{space 2} 2.674419{col 28}{space 2} .0575436{col 39}{space 1}   46.48{col 48}{space 3}0.000{col 56}{space 4} 2.561548{col 69}{space 3}  2.78729
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins i.message, pwcompare(effects)
{res}
{txt}{col 1}Pairwise comparisons of adjusted predictions{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:1,563}
{txt}{col 1}Model VCE: {res:OLS}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}

{res}{txt}{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44} Delta-method{col 55}    Una{col 64}djusted{col 72}          Una{col 85}djusted
{col 32}{c |}   Contrast{col 44}   std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}message {c |}
{space 4}Pro_moral vs Pro_nonmoral  {c |}{col 32}{res}{space 2}  .177913{col 44}{space 2} .0814316{col 55}{space 1}    2.18{col 64}{space 3}0.029{col 72}{space 4}  .018186{col 85}{space 3}   .33764
{txt}Anti_nonmoral vs Pro_nonmoral  {c |}{col 32}{res}{space 2} .3034139{col 44}{space 2} .0804212{col 55}{space 1}    3.77{col 64}{space 3}0.000{col 72}{space 4} .1456688{col 85}{space 3}  .461159
{txt}{space 3}Anti_moral vs Pro_nonmoral  {c |}{col 32}{res}{space 2} .2292272{col 44}{space 2} .0815377{col 55}{space 1}    2.81{col 64}{space 3}0.005{col 72}{space 4} .0692921{col 85}{space 3} .3891624
{txt}{space 3}Anti_nonmoral vs Pro_moral  {c |}{col 32}{res}{space 2} .1255009{col 44}{space 2} .0804745{col 55}{space 1}    1.56{col 64}{space 3}0.119{col 72}{space 4}-.0323488{col 85}{space 3} .2833506
{txt}{space 6}Anti_moral vs Pro_moral  {c |}{col 32}{res}{space 2} .0513142{col 44}{space 2} .0815903{col 55}{space 1}    0.63{col 64}{space 3}0.529{col 72}{space 4}-.1087241{col 85}{space 3} .2113525
{txt}{space 2}Anti_moral vs Anti_nonmoral  {c |}{col 32}{res}{space 2}-.0741867{col 44}{space 2} .0805819{col 55}{space 1}   -0.92{col 64}{space 3}0.357{col 72}{space 4}-.2322469{col 85}{space 3} .0838736
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. marginsplot, horizontal unique recast(scatter) yscale(reverse) xline(0) xscale(range(-0.3 0.5)) xlab(-0.3 (0.2) 0.5) ylab(1"Pro_moral_vs_Pro_non_moral" 2"Anti_non_moral_vs_Pro_non_moral" 3"Anti_moral_vs_Pro_non_moral" 4"Anti_non_moral_vs_Pro_moral" 5"Anti_moral_vs_Pro_moral" 6"Anti_moral_vs_Anti_non_moral") xtitle("") ytitle("")
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:_pw}{p_end}

{text}{p 6 10 2}i{bf:_pw} enumerates all pairwise comparisons; {bf:_pw0} enumerates the reference categories; {bf:_pw1} enumerates the comparison categories.{p_end}
{res}{txt}
{com}. graph export figa21.png
{txt}{p 0 4 2}
file {bf}
figa21.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. ***Table A3.1.***
. putdocx begin
{res}{txt}
{com}. ologit q15 i.message

{res}{txt}Iteration 0:{space 2}Log likelihood = {res:-2344.3599}  
Iteration 1:{space 2}Log likelihood = {res:-2336.8607}  
Iteration 2:{space 2}Log likelihood = {res:-2336.8556}  
Iteration 3:{space 2}Log likelihood = {res:-2336.8556}  
{res}
{txt}{col 1}Ordered logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:1,563}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:15.01}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0018}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-2336.8556}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0032}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           q15{col 16}{c |} Coefficient{col 28}  Std. err.{col 40}      z{col 48}   P>|z|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}message {c |}
{space 4}Pro_moral  {c |}{col 16}{res}{space 2} .2690781{col 28}{space 2} .1265306{col 39}{space 1}    2.13{col 48}{space 3}0.033{col 56}{space 4} .0210828{col 69}{space 3} .5170735
{txt}Anti_nonmoral  {c |}{col 16}{res}{space 2}  .477235{col 28}{space 2} .1273093{col 39}{space 1}    3.75{col 48}{space 3}0.000{col 56}{space 4} .2277134{col 69}{space 3} .7267566
{txt}{space 3}Anti_moral  {c |}{col 16}{res}{space 2} .3465156{col 28}{space 2} .1305871{col 39}{space 1}    2.65{col 48}{space 3}0.008{col 56}{space 4} .0905695{col 69}{space 3} .6024617
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}/cut1 {c |}{col 16}{res}{space 2}-1.490929{col 28}{space 2} .1028592{col 56}{space 4} -1.69253{col 69}{space 3}-1.289329
{txt}{space 9}/cut2 {c |}{col 16}{res}{space 2}  -.32001{col 28}{space 2} .0923736{col 56}{space 4} -.501059{col 69}{space 3} -.138961
{txt}{space 9}/cut3 {c |}{col 16}{res}{space 2} 1.207736{col 28}{space 2} .0973071{col 56}{space 4} 1.017017{col 69}{space 3} 1.398454
{txt}{space 9}/cut4 {c |}{col 16}{res}{space 2}  2.78166{col 28}{space 2} .1256406{col 56}{space 4}  2.53541{col 69}{space 3} 3.027911
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. putdocx table tablea31 = etable, width(100%)
{res}{txt}
{com}. putdocx save tablea31
{res}successfully created {browse "C:/Users/au282143/Desktop/PSRM/Replication/tablea31.docx":"C:/Users/au282143/Desktop/PSRM/Replication/tablea31.docx"}
{txt}
{com}. 
. ***Figure A3.1.***
. ologit q15 ib2.message

{res}{txt}Iteration 0:{space 2}Log likelihood = {res:-2344.3599}  
Iteration 1:{space 2}Log likelihood = {res:-2336.8607}  
Iteration 2:{space 2}Log likelihood = {res:-2336.8556}  
Iteration 3:{space 2}Log likelihood = {res:-2336.8556}  
{res}
{txt}{col 1}Ordered logistic regression{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:1,563}
{txt}{col 57}{lalign 13:LR chi2({res:3})}{col 70} = {res}{ralign 6:15.01}
{txt}{col 57}{lalign 13:Prob > chi2}{col 70} = {res}{ralign 6:0.0018}
{txt}{col 1}{lalign 14:Log likelihood}{col 15} = {res}{ralign 10:-2336.8556}{txt}{col 57}{lalign 13:Pseudo R2}{col 70} = {res}{ralign 6:0.0032}

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           q15{col 16}{c |} Coefficient{col 28}  Std. err.{col 40}      z{col 48}   P>|z|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}message {c |}
{space 1}Pro_nonmoral  {c |}{col 16}{res}{space 2}-.2690781{col 28}{space 2} .1265306{col 39}{space 1}   -2.13{col 48}{space 3}0.033{col 56}{space 4}-.5170735{col 69}{space 3}-.0210828
{txt}Anti_nonmoral  {c |}{col 16}{res}{space 2} .2081569{col 28}{space 2} .1269406{col 39}{space 1}    1.64{col 48}{space 3}0.101{col 56}{space 4}-.0406421{col 69}{space 3} .4569558
{txt}{space 3}Anti_moral  {c |}{col 16}{res}{space 2} .0774375{col 28}{space 2} .1304085{col 39}{space 1}    0.59{col 48}{space 3}0.553{col 56}{space 4}-.1781584{col 69}{space 3} .3330334
{txt}{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}/cut1 {c |}{col 16}{res}{space 2}-1.760007{col 28}{space 2} .1053191{col 56}{space 4}-1.966429{col 69}{space 3}-1.553586
{txt}{space 9}/cut2 {c |}{col 16}{res}{space 2}-.5890881{col 28}{space 2} .0932446{col 56}{space 4}-.7718442{col 69}{space 3}-.4063321
{txt}{space 9}/cut3 {c |}{col 16}{res}{space 2} .9386575{col 28}{space 2} .0953979{col 56}{space 4}  .751681{col 69}{space 3} 1.125634
{txt}{space 9}/cut4 {c |}{col 16}{res}{space 2} 2.512582{col 28}{space 2} .1232643{col 56}{space 4} 2.270989{col 69}{space 3} 2.754176
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(message) predict(outcome(1)) predict(outcome(5))
{res}
{txt}{col 1}Conditional marginal effects{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:1,563}
{txt}{col 1}Model VCE: {res:OIM}

{txt}{p2colset 1 12 12 2}{...}
{p2col:dy/dx wrt:}{res:1.message 3.message 4.message}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 13 13 2}{...}
{p2col:{txt:1._predict:}}{res:Pr(q15==1), predict(outcome(1))}{p_end}
{p2col:{txt:2._predict:}}{res:Pr(q15==5), predict(outcome(5))}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}      dy/dx{col 26}   std. err.{col 38}      z{col 46}   P>|z|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}1.message    {txt}{c |}
{space 4}_predict {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .0369929{col 26}{space 2} .0174838{col 37}{space 1}    2.12{col 46}{space 3}0.034{col 54}{space 4} .0027253{col 67}{space 3} .0712604
{txt}{space 10}2  {c |}{col 14}{res}{space 2}-.0166575{col 26}{space 2} .0079803{col 37}{space 1}   -2.09{col 46}{space 3}0.037{col 54}{space 4}-.0322985{col 67}{space 3}-.0010165
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}2.message   {col 14}{txt}{c |}  (base outcome)
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}3.message    {txt}{c |}
{space 4}_predict {c |}
{space 10}1  {c |}{col 14}{res}{space 2}-.0242032{col 26}{space 2} .0148193{col 37}{space 1}   -1.63{col 46}{space 3}0.102{col 54}{space 4}-.0532486{col 67}{space 3} .0048422
{txt}{space 10}2  {c |}{col 14}{res}{space 2} .0157763{col 26}{space 2} .0097084{col 37}{space 1}    1.63{col 46}{space 3}0.104{col 54}{space 4}-.0032518{col 67}{space 3} .0348044
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}4.message    {txt}{c |}
{space 4}_predict {c |}
{space 10}1  {c |}{col 14}{res}{space 2}-.0094357{col 26}{space 2} .0158769{col 37}{space 1}   -0.59{col 46}{space 3}0.552{col 54}{space 4}-.0405538{col 67}{space 3} .0216825
{txt}{space 10}2  {c |}{col 14}{res}{space 2} .0055509{col 26}{space 2} .0093744{col 37}{space 1}    0.59{col 46}{space 3}0.554{col 54}{space 4}-.0128227{col 67}{space 3} .0239245
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 78}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. marginsplot, unique recast(scatter) yscale(reverse) yline(0) yscale(range(-0.1 (0.05) 0.1)) ylab(-0.1 (0.05) 0.1) ytitle("Effects on probability") xlab(1"Pro_non_moral" 2"Pro_moral" 3"Anti_non_moral" 4"Anti_moral") xtitle("") plot1opts(msymbol(Oh)) plot2opts(mcolor(black) msymbol(D)) ciopts(color(black))
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:_deriv}{p_end}
{res}{txt}
{com}. graph export figa31.png
{txt}{p 0 4 2}
file {bf}
figa31.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. ***Table A4.1.***
. putdocx begin 
{res}{txt}
{com}. reg q15 i.message i.partysponsor

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,563
{txt}{hline 13}{c +}{hline 34}   F(4, 1558)      = {res}     3.83
{txt}       Model {c |} {res} 19.6552925         4  4.91382311   {txt}Prob > F        ={res}    0.0042
{txt}    Residual {c |} {res}  1997.7932     1,558  1.28228062   {txt}R-squared       ={res}    0.0097
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0072
{txt}       Total {c |} {res}  2017.4485     1,562  1.29158034   {txt}Root MSE        =   {res} 1.1324

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           q15{col 16}{c |} Coefficient{col 28}  Std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}message {c |}
{space 4}Pro_moral  {c |}{col 16}{res}{space 2} .1778766{col 28}{space 2} .0814634{col 39}{space 1}    2.18{col 48}{space 3}0.029{col 56}{space 4} .0180871{col 69}{space 3}  .337666
{txt}Anti_nonmoral  {c |}{col 16}{res}{space 2} .3034324{col 28}{space 2} .0804485{col 39}{space 1}    3.77{col 48}{space 3}0.000{col 56}{space 4} .1456338{col 69}{space 3} .4612311
{txt}{space 3}Anti_moral  {c |}{col 16}{res}{space 2} .2292413{col 28}{space 2} .0815647{col 39}{space 1}    2.81{col 48}{space 3}0.005{col 56}{space 4} .0692532{col 69}{space 3} .3892295
{txt}{space 14} {c |}
{space 2}partysponsor {c |}
{space 6}Venstre  {c |}{col 16}{res}{space 2} .0021646{col 28}{space 2} .0572966{col 39}{space 1}    0.04{col 48}{space 3}0.970{col 56}{space 4} -.110222{col 69}{space 3} .1145513
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 2.673339{col 28}{space 2} .0642641{col 39}{space 1}   41.60{col 48}{space 3}0.000{col 56}{space 4} 2.547286{col 69}{space 3} 2.799392
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. putdocx table tablea41 = etable, width(100%)
{res}{txt}
{com}. putdocx save tablea41
{res}successfully created {browse "C:/Users/au282143/Desktop/PSRM/Replication/tablea41.docx":"C:/Users/au282143/Desktop/PSRM/Replication/tablea41.docx"}
{txt}
{com}. 
. ***Figure A4.1.***
. reg q15 i.message i.partysponsor

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     1,563
{txt}{hline 13}{c +}{hline 34}   F(4, 1558)      = {res}     3.83
{txt}       Model {c |} {res} 19.6552925         4  4.91382311   {txt}Prob > F        ={res}    0.0042
{txt}    Residual {c |} {res}  1997.7932     1,558  1.28228062   {txt}R-squared       ={res}    0.0097
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.0072
{txt}       Total {c |} {res}  2017.4485     1,562  1.29158034   {txt}Root MSE        =   {res} 1.1324

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           q15{col 16}{c |} Coefficient{col 28}  Std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}message {c |}
{space 4}Pro_moral  {c |}{col 16}{res}{space 2} .1778766{col 28}{space 2} .0814634{col 39}{space 1}    2.18{col 48}{space 3}0.029{col 56}{space 4} .0180871{col 69}{space 3}  .337666
{txt}Anti_nonmoral  {c |}{col 16}{res}{space 2} .3034324{col 28}{space 2} .0804485{col 39}{space 1}    3.77{col 48}{space 3}0.000{col 56}{space 4} .1456338{col 69}{space 3} .4612311
{txt}{space 3}Anti_moral  {c |}{col 16}{res}{space 2} .2292413{col 28}{space 2} .0815647{col 39}{space 1}    2.81{col 48}{space 3}0.005{col 56}{space 4} .0692532{col 69}{space 3} .3892295
{txt}{space 14} {c |}
{space 2}partysponsor {c |}
{space 6}Venstre  {c |}{col 16}{res}{space 2} .0021646{col 28}{space 2} .0572966{col 39}{space 1}    0.04{col 48}{space 3}0.970{col 56}{space 4} -.110222{col 69}{space 3} .1145513
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 2.673339{col 28}{space 2} .0642641{col 39}{space 1}   41.60{col 48}{space 3}0.000{col 56}{space 4} 2.547286{col 69}{space 3} 2.799392
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins i.message i.partysponsor, pwcompare(effects)
{res}
{txt}{col 1}Pairwise comparisons of predictive margins{col 58}{lalign 13:Number of obs}{col 71} = {res}{ralign 5:1,563}
{txt}{col 1}Model VCE: {res:OLS}

{txt}{p2colset 1 13 13 2}{...}
{p2col:Expression:}{res:Linear prediction, predict()}{p_end}
{p2colreset}{...}

{res}{txt}{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44} Delta-method{col 55}    Una{col 64}djusted{col 72}          Una{col 85}djusted
{col 32}{c |}   Contrast{col 44}   std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}message {c |}
{space 4}Pro_moral vs Pro_nonmoral  {c |}{col 32}{res}{space 2} .1778766{col 44}{space 2} .0814634{col 55}{space 1}    2.18{col 64}{space 3}0.029{col 72}{space 4} .0180871{col 85}{space 3}  .337666
{txt}Anti_nonmoral vs Pro_nonmoral  {c |}{col 32}{res}{space 2} .3034324{col 44}{space 2} .0804485{col 55}{space 1}    3.77{col 64}{space 3}0.000{col 72}{space 4} .1456338{col 85}{space 3} .4612311
{txt}{space 3}Anti_moral vs Pro_nonmoral  {c |}{col 32}{res}{space 2} .2292413{col 44}{space 2} .0815647{col 55}{space 1}    2.81{col 64}{space 3}0.005{col 72}{space 4} .0692532{col 85}{space 3} .3892295
{txt}{space 3}Anti_nonmoral vs Pro_moral  {c |}{col 32}{res}{space 2} .1255559{col 44}{space 2} .0805134{col 55}{space 1}    1.56{col 64}{space 3}0.119{col 72}{space 4}-.0323703{col 85}{space 3}  .283482
{txt}{space 6}Anti_moral vs Pro_moral  {c |}{col 32}{res}{space 2} .0513648{col 44}{space 2} .0816274{col 55}{space 1}    0.63{col 64}{space 3}0.529{col 72}{space 4}-.1087464{col 85}{space 3}  .211476
{txt}{space 2}Anti_moral vs Anti_nonmoral  {c |}{col 32}{res}{space 2}-.0741911{col 44}{space 2} .0806078{col 55}{space 1}   -0.92{col 64}{space 3}0.358{col 72}{space 4}-.2323023{col 85}{space 3} .0839201
{txt}{space 30} {c |}
{space 18}partysponsor {c |}
{space 12}Venstre vs SocDem  {c |}{col 32}{res}{space 2} .0021646{col 44}{space 2} .0572966{col 55}{space 1}    0.04{col 64}{space 3}0.970{col 72}{space 4} -.110222{col 85}{space 3} .1145513
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. marginsplot, horizontal unique recast(scatter) yscale(reverse) xline(0) xscale(range(-0.3 0.5)) xlab(-0.3 (0.2) 0.5) ylab(1"Pro_moral_vs_Pro_non_moral" 2"Anti_non_moral_vs_Pro_non_moral" 3"Anti_moral_vs_Pro_non_moral" 4"Anti_non_moral_vs_Pro_moral" 5"Anti_moral_vs_Pro_moral" 6"Anti_moral_vs_Anti_non_moral" 7"Venstre_vs_Socialdemokratiet") xtitle("") ytitle("")
{res}
{text}{p 0 0 2}Variables that uniquely identify margins: {bf:_pw}{p_end}

{text}{p 6 10 2}i{bf:_pw} enumerates all pairwise comparisons; {bf:_pw0} enumerates the reference categories; {bf:_pw1} enumerates the comparison categories.{p_end}
{res}{txt}
{com}. graph export figa41.png
{txt}{p 0 4 2}
file {bf}
figa41.png{rm}
saved as
PNG
format
{p_end}

{com}. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\au282143\Desktop\PSRM\Replication\Log for Are Pro-Im.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}10 Jul 2024, 10:11:14
{txt}{.-}
{smcl}
{txt}{sf}{ul off}